Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals
Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distrib...
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ftdans:oai:easy.dans.knaw.nl:easy-dataset:108343 2023-07-02T03:30:57+02:00 Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals Mäkinen, Jussi 2018-06-21T15:38:20.000+02:00 http://nbn-resolving.org/urn:nbn:nl:ui:13-ae-g1mu https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:108343 unknown doi:10.5061/dryad.22c867m/1 doi:10.1111/ddi.12776 http://nbn-resolving.org/urn:nbn:nl:ui:13-ae-g1mu doi:10.5061/dryad.22c867m https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:108343 OPEN_ACCESS: The data are archived in Easy, they are accessible elsewhere through the DOI https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf Life sciences medicine and health care 2018 ftdans https://doi.org/10.5061/dryad.22c867m/110.1111/ddi.1277610.5061/dryad.22c867m 2023-06-13T13:30:24Z Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distributions and to analyze whether their distributions have shifted along with environmental changes. Location: Arctic shelf area. The Kara Sea. Methods: Our literature search focused on survey data regarding polar bears (Ursus maritimus), Atlantic walruses (Odobenus rosmarus rosmarus) and ringed seals (Phoca hispida). We mapped the data on a grid and built a hierarchical Poisson point process model to analyze species’ densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results: The most important covariates explaining AMMs’ relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17-yearlong study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions: Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species’ distributions compared to a solely environmental model. The decreasing ice cover seems to have led to changes ... Other/Unknown Material Arctic marine mammals Arctic Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* Data Archiving and Networked Services (DANS): EASY (KNAW - Koninklijke Nederlandse Akademie van Wetenschappen) Arctic Kara Sea |
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Open Polar |
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Data Archiving and Networked Services (DANS): EASY (KNAW - Koninklijke Nederlandse Akademie van Wetenschappen) |
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Life sciences medicine and health care |
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Life sciences medicine and health care Mäkinen, Jussi Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
topic_facet |
Life sciences medicine and health care |
description |
Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distributions and to analyze whether their distributions have shifted along with environmental changes. Location: Arctic shelf area. The Kara Sea. Methods: Our literature search focused on survey data regarding polar bears (Ursus maritimus), Atlantic walruses (Odobenus rosmarus rosmarus) and ringed seals (Phoca hispida). We mapped the data on a grid and built a hierarchical Poisson point process model to analyze species’ densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results: The most important covariates explaining AMMs’ relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17-yearlong study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions: Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species’ distributions compared to a solely environmental model. The decreasing ice cover seems to have led to changes ... |
author |
Mäkinen, Jussi |
author_facet |
Mäkinen, Jussi |
author_sort |
Mäkinen, Jussi |
title |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_short |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_full |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_fullStr |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_full_unstemmed |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_sort |
data from: hierarchical bayesian model reveals the distributional shifts of arctic marine mammals |
publishDate |
2018 |
url |
http://nbn-resolving.org/urn:nbn:nl:ui:13-ae-g1mu https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:108343 |
geographic |
Arctic Kara Sea |
geographic_facet |
Arctic Kara Sea |
genre |
Arctic marine mammals Arctic Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* |
genre_facet |
Arctic marine mammals Arctic Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* |
op_relation |
doi:10.5061/dryad.22c867m/1 doi:10.1111/ddi.12776 http://nbn-resolving.org/urn:nbn:nl:ui:13-ae-g1mu doi:10.5061/dryad.22c867m https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:108343 |
op_rights |
OPEN_ACCESS: The data are archived in Easy, they are accessible elsewhere through the DOI https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf |
op_doi |
https://doi.org/10.5061/dryad.22c867m/110.1111/ddi.1277610.5061/dryad.22c867m |
_version_ |
1770275216471097344 |